Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch

Last update: Dec 31, 2022

Overview

Get SH*T Done with PyTorch

Learn how to solve real-world problems with Deep Learning models (NLP, Computer Vision, and Time Series). Go from prototyping to deployment with PyTorch and Python!

Read the book here

📖 Read for FREE

The whole book can be read using the links below. Each part contains a notebook that you can find in this repository.

Consider buying the book if you want to support my work. Thanks for stopping by! 🤗

Owner

Venelin Valkov

GitHub Repository https://www.curiousily.com/

The guide to tackle with the Text Summarization

1.2k Dec 30, 2022

Header-only C++ HNSW implementation with python bindings

Hnswlib - fast approximate nearest neighbor search Header-only C++ HNSW implementation with python bindings. NEWS: version 0.6 Thanks to (@dyashuni) h

2.3k Jan 05, 2023

Fake news detector filters - Smart filter project allow to classify the quality of information and web pages

fake-news-detector-1.0 Lists, lists and more lists... Spam filter list, quality keyword list, stoplist list, top-domains urls list, news agencies webs

1 Jan 04, 2022

Toward a Visual Concept Vocabulary for GAN Latent Space, ICCV 2021

Toward a Visual Concept Vocabulary for GAN Latent Space Code and data from the ICCV 2021 paper Sarah Schwettmann, Evan Hernandez, David Bau, Samuel Kl

13 Dec 23, 2022

MILES is a multilingual text simplifier inspired by LSBert - A BERT-based lexical simplification approach proposed in 2018. Unlike LSBert, MILES uses the bert-base-multilingual-uncased model, as well as simple language-agnostic approaches to complex word identification (CWI) and candidate ranking.

MILES Multilingual Lexical Simplifier Explore the docs » Read LSBert Paper · Report Bug · Request Feature About The Project MILES is a multilingual te

45 Oct 19, 2022

NLP, before and after spaCy

textacy: NLP, before and after spaCy textacy is a Python library for performing a variety of natural language processing (NLP) tasks, built on the hig

2k Jan 04, 2023

Generate a cool README/About me page for your Github Profile

Github Profile README/ About Me Generator 💯 This webapp lets you build a cool README for your profile. A few inputs + ~15 mins = Your Github Profile

179 Jan 07, 2023

Code to reprudece NeurIPS paper: Accelerated Sparse Neural Training: A Provable and Efficient Method to Find N:M Transposable Masks

Accelerated Sparse Neural Training: A Provable and Efficient Method to FindN:M Transposable Masks Recently, researchers proposed pruning deep neural n

4 Feb 23, 2022

[NeurIPS 2021] Code for Learning Signal-Agnostic Manifolds of Neural Fields

Learning Signal-Agnostic Manifolds of Neural Fields This is the uncleaned code for the paper Learning Signal-Agnostic Manifolds of Neural Fields. The

60 Dec 12, 2022

skweak: A software toolkit for weak supervision applied to NLP tasks

Labelled data remains a scarce resource in many practical NLP scenarios. This is especially the case when working with resource-poor languages (or text domains), or when using task-specific labels wi

850 Dec 28, 2022

OpenChat: Opensource chatting framework for generative models

OpenChat is opensource chatting framework for generative models.

427 Jan 06, 2023

Kerberoast with ACL abuse capabilities

targetedKerberoast targetedKerberoast is a Python script that can, like many others (e.g. GetUserSPNs.py), print "kerberoast" hashes for user accounts

213 Dec 22, 2022

Negative sampling for solving the unlabeled entity problem in NER. ICLR-2021 paper: Empirical Analysis of Unlabeled Entity Problem in Named Entity Recognition.

Negative Sampling for NER Unlabeled entity problem is prevalent in many NER scenarios (e.g., weakly supervised NER). Our paper in ICLR-2021 proposes u

128 Dec 29, 2022